Topographical models of geographical areas may be used for many applications. For example, topographical models may be used in flight simulators and for planning military missions. Furthermore, topographical models of man-made structures (e.g., cities) may be extremely helpful in applications such as cellular antenna placement, urban planning, disaster preparedness and analysis, and mapping, for example.
Various types and methods for making topographical models are presently being used. One common topographical model is the digital elevation map (DEM). A DEM is a sampled matrix representation of a geographical area which may be generated in an automated fashion by a computer. In a DEM, coordinate points are made to correspond with a height value. DEMs are typically used for modeling terrain where the transitions between different elevations (e.g., valleys, mountains, etc.) are generally smooth from one to a next. That is, DEMs typically model terrain as a plurality of curved surfaces and any discontinuities therebetween are thus “smoothed” over. Thus, in a typical DEM no distinct objects are present on the terrain.
One particularly advantageous 3D site modeling product is RealSite® from the present Assignee Harris Corp. RealSite® may be used to register overlapping images of a geographical area of interest, and extract high resolution DEMs using stereo and nadir view techniques. RealSite® provides a semi-automated process for making three-dimensional (3D) topographical models of geographical areas, including cities, that have accurate textures and structure boundaries. Moreover, RealSite® models are geospatially accurate. That is, the location of any given point within the model corresponds to an actual location in the geographical area with very high accuracy The data used to generate RealSite® models may include aerial and satellite photography, electro-optical, infrared, and light detection and ranging (LIDAR).
Another advantageous approach for generating 3D site models is set forth in U.S. Pat. No. 6,654,690 to Rahmes et al., which is also assigned to the present Assignee and is hereby incorporated herein in its entirety by reference. This patent discloses an automated method for making a topographical model of an area including terrain and buildings thereon based upon randomly spaced data of elevation versus position. The method includes processing the randomly spaced data to generate gridded data of elevation versus position conforming to a predetermined position grid, processing the gridded data to distinguish building data from terrain data, and performing polygon extraction for the building data to make the topographical model of the area including terrain and buildings thereon.
While the above-noted approaches provide exceptional 3D models of urban areas with accurate and realistic cultural (e.g., building) feature detail, in some applications it may be desirable to produce a topographical model of a geographical area of interest without the cultural features otherwise present in the area of interest. Yet, once the cultural features are identified and extracted from the terrain data, there may be voids left in the resulting DEM. Moreover, in some situations it may be desirable to focus on cultural features from an area of interest, but foliage, etc., may obscure portions of one or more cultural features that will similarly result in voids in the cultural feature when the foliage is extracted.
Various interpolation techniques are generally used for filling in missing data in a data field. One such technique is sinc interpolation, which assumes that a signal is band-limited. While this approach is well suited for communication and audio signals, it may not be well suited for 3D data models. Another approach is polynomial interpolation. This approach is sometimes difficult to implement because the computational overhead may become overly burdensome for higher order polynomials, which may be necessary to provide desired accuracy.
One additional interpolation approach is spline interpolation. While this approach may provide a relatively high reconstruction accuracy, this approach may be problematic to implement in a 3D data model because of the difficultly in solving a global spline over the entire model, and because the required matrices may be ill-conditioned. One further drawback of such conventional techniques is that they tend to blur edge content, which may be a significant problem in a 3D topographical model.
Another approach for filling in regions within an image is set forth in U.S. Pat. No. 6,987,520 to Criminisi et al. This patent discloses an examplar-based filling system which identifies appropriate filling material to replace a destination region in an image and fills the destination region using this material. This is done to alleviate or minimize the amount of manual editing required to fill a destination region in an image. Tiles of image data are “borrowed” from the proximity of the destination region or some other source to generate new image data to fill in the region. Destination regions may be designated by user input (e.g., selection of an image region by a user) or by other means (e.g., specification of a color or feature to be replaced). In addition, the order in which the destination region is filled by example tiles may be configured to emphasize the continuity of linear structures and composite textures using a type of isophote-driven image-sampling process.
Another way in which geospatial model data can end up with voids therein is when the data is collected in the frequency domain, as is the case with Synthetic Aperture Radar (SAR) data collection. That is, a SAR returns a map or representation of radar reflectivity including both amplitude and phase over a plurality of different frequencies. However, due to interference from existing signal sources, during some SAR scans certain frequency bands may experience interference in the resulting SAR data. Moreover, the operator of the SAR may have to intentionally omit or block certain frequency bands in certain geographical areas from the scan to avoid interfering with such communication sources. Further, hardware malfunctions may result in pulse dropouts. In each of these cases, the result is that the frequency domain representation of the area of interest will have gaps or voids therein, which when converted to the spatial domain cause the resulting geospatial model image to be distorted.
Generally speaking, various approaches have been used to address the effects of interference in frequency domain data. One approach is to use linear interpolation. Super resolution and/or iterative convolution techniques have also been used which assume a point like target in the image. Moreover, hardware approaches have also been implemented to alter mode hopping to avoid interference or listening on pilot pulses to characterize the interference.
Another approach to interference suppression in SAP images is set forth in an article entitled “Interference Suppression in Synthesized SAR Images” by Reigber et al., IEEE Geoscience and Remote Sensing Letters, vol. 2, no. 1, January 2005. This article proposes an interference suppression approach that relies on the transformation of synthesized SAR images into a representation where common raw-data interference filtering methods can be applied. More particularly, this approach uses a posteriori filtering.
Despite the advantages such prior art approaches may provide in certain applications, further advancements may be desirable for filling voids in geospatial model data.